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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Detection of atrial fibrillation using discrete-state Markov models and Random Forests
Vignesh Kalidas, Lakshman S. Tamil
Computers in Biology and Medicine (2019) Vol. 113, pp. 103386-103386
Closed Access | Times Cited: 45

Showing 1-25 of 45 citing articles:

A Deep Learning Approach for Atrial Fibrillation Classification Using Multi-Feature Time Series Data from ECG and PPG
Bader Aldughayfiq, Farzeen Ashfaq, N. Z. Jhanjhi, et al.
Diagnostics (2023) Vol. 13, Iss. 14, pp. 2442-2442
Open Access | Times Cited: 22
An intelligent computer-aided approach for atrial fibrillation and atrial flutter signals classification using modified bidirectional LSTM network
Jibin Wang
Information Sciences (2021) Vol. 574, pp. 320-332
Closed Access | Times Cited: 52
Automated detection of atrial fibrillation and atrial flutter in ECG signals based on convolutional and improved Elman neural network
Jibin Wang
Knowledge-Based Systems (2019) Vol. 193, pp. 105446-105446
Closed Access | Times Cited: 46
Atrial fibrillation detection using heart rate variability and atrial activity: A hybrid approach
G. H. Hirsch, Søren Højgaard Jensen, Erik S. Poulsen, et al.
Expert Systems with Applications (2020) Vol. 169, pp. 114452-114452
Open Access | Times Cited: 40
Detection of Paroxysmal Atrial Fibrillation from Dynamic ECG Recordings Based on a Deep Learning Model
Yating Hu, Tengfei Feng, Miao Wang, et al.
Journal of Personalized Medicine (2023) Vol. 13, Iss. 5, pp. 820-820
Open Access | Times Cited: 13
Artificial intelligence for atrial fibrillation detection, prediction, and treatment: A systematic review of the last decade (2013–2023)
Massimo Salvi, Madhav R. Acharya, Silvia Seoni, et al.
Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery (2024) Vol. 14, Iss. 3
Closed Access | Times Cited: 4
A novel bidirectional LSTM network based on scale factor for atrial fibrillation signals classification
Kunye Feng, Zile Fan
Biomedical Signal Processing and Control (2022) Vol. 76, pp. 103663-103663
Closed Access | Times Cited: 21
Enhancing Atrial Fibrillation detection accuracy: A wavelet transform filtered single lead ECG signal analysis with artificial neural networks and novel feature extraction
D S Duranta, Md Shahin Ali, Abhilash Arjan Das, et al.
Machine Learning with Applications (2023) Vol. 12, pp. 100472-100472
Open Access | Times Cited: 10
Atrial fibrillation detection with and without atrial activity analysis using lead-I mobile ECG technology
Gergely Tuboly, György Kozmann, Orsolya Kiss, et al.
Biomedical Signal Processing and Control (2021) Vol. 66, pp. 102462-102462
Open Access | Times Cited: 22
An Effective Atrial Fibrillation Detection from Short Single-Lead Electrocardiogram Recordings Using MCNN-BLSTM Network
Hongpo Zhang, Hongzhuang Gu, Junli Gao, et al.
Algorithms (2022) Vol. 15, Iss. 12, pp. 454-454
Open Access | Times Cited: 15
Automated detection of premature ventricular contraction based on the improved gated recurrent unit network
Jibin Wang
Computer Methods and Programs in Biomedicine (2021) Vol. 208, pp. 106284-106284
Closed Access | Times Cited: 19
MMA-RNN: A multi-level multi-task attention-based recurrent neural network for discrimination and localization of atrial fibrillation
Yifan Sun, Jingyan Shen, Yunfan Jiang, et al.
Biomedical Signal Processing and Control (2023) Vol. 89, pp. 105747-105747
Open Access | Times Cited: 7
An atrial fibrillation classification method based on an outlier data filtering strategy and modified residual block of the feature pyramid network
Hongpo Zhang, Hongzhuang Gu, Guanhe Chen, et al.
Biomedical Signal Processing and Control (2024) Vol. 92, pp. 106107-106107
Closed Access | Times Cited: 2
An Attribute-Decoupled Model for Onset Identification of Atrial Fibrillation in Single-Lead Electrocardiograms
Q Li, Xingyao Wang, Hongxiang Gao, et al.
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-14
Closed Access | Times Cited: 2
A deep learning refinement strategy based on efficient channel attention for atrial fibrillation and atrial flutter signals identification
Jibin Wang, Xiaotai Wu
Applied Soft Computing (2022) Vol. 130, pp. 109552-109552
Closed Access | Times Cited: 9
An improved deep learning approach based on exponential moving average algorithm for atrial fibrillation signals identification
Jibin Wang, Shuo Zhang
Neurocomputing (2022) Vol. 513, pp. 127-136
Closed Access | Times Cited: 9
Optimizing random forest classifier with Jenesis-index on an imbalanced dataset
Joylin Zeffora, R. Shobarani
Indonesian Journal of Electrical Engineering and Computer Science (2022) Vol. 26, Iss. 1, pp. 505-505
Open Access | Times Cited: 8
Stacked machine learning models to classify atrial disorders based on clinical ECG features: a method to predict early atrial fibrillation
Dhananjay Budaraju, Bala Chakravarthy Neelapu, Kunal Pal, et al.
Biomedical Engineering / Biomedizinische Technik (2023) Vol. 68, Iss. 4, pp. 393-409
Closed Access | Times Cited: 4
An intelligent computer-aided diagnosis method for paroxysmal atrial fibrillation patients with nondiagnostic ECG signals
Muqing Deng, Kengren Chen, Dehua Huang, et al.
Biomedical Signal Processing and Control (2023) Vol. 88, pp. 105683-105683
Closed Access | Times Cited: 4
An Improved Approach for Atrial Fibrillation Detection in Long-Term ECG Using Decomposition Transforms and Least-Squares Support Vector Machine
Tomasz Pander
Applied Sciences (2023) Vol. 13, Iss. 22, pp. 12187-12187
Open Access | Times Cited: 4
Atrial Fibrillation Detection Based on Deep Learning Models
Adrian Iftene, Alexandru Burlacu, Daniela Gîfu
Procedia Computer Science (2022) Vol. 207, pp. 3752-3760
Open Access | Times Cited: 6
ECG segmentation algorithm based on bidirectional hidden semi-Markov model
Rui Huo, Liting Zhang, Feifei Liu, et al.
Computers in Biology and Medicine (2022) Vol. 150, pp. 106081-106081
Closed Access | Times Cited: 5
Machine learning based hybrid anomaly detection technique for automatic diagnosis of cardiovascular diseases using cardiac sympathetic nerve activity and electrocardiogram
Merve Begüm Terzı, Orhan Arıkan
Biomedical Engineering / Biomedizinische Technik (2023) Vol. 69, Iss. 1, pp. 79-109
Closed Access | Times Cited: 2
AF episodes recognition using optimized time-frequency features and cost-sensitive SVM
Hocine Hamil, Zahia Zidelmal, Mohamed Salah Azzaz, et al.
Physical and Engineering Sciences in Medicine (2021) Vol. 44, Iss. 3, pp. 613-624
Closed Access | Times Cited: 5
A Hybrid Attention-based LSTM-XGBoost Model for Detection of ECG-based Atrial Fibrillation
Furkan BALCI
Gazi University Journal of Science Part A Engineering and Innovation (2022) Vol. 9, Iss. 3, pp. 199-210
Open Access | Times Cited: 3
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